All you need to know
ABOUT RENS VAN DE SCHOOT
Prof. Dr. Rens van de Schoot works as full professor 'Statistics for Small Data Sets' at Utrecht University in the Netherlands and as extra-ordinary professor North-West University in South-Africa. He is also program director of the research master 'Methodology and Statistics for the Behavioural, Biomedical and Social Sciences' and coordinator of the post-graduate program at the department of Methods and Statistics
His main research projects are (1) ASReview: Automated systematic text reviewing by using Deep Learning and Active Learning; (2) integrating expert (=teacher) knowledge in end of primary school testing; (3) solutions for small data sets (S4) in the field of structural equation modelling with solutions in the areas of expert elicitation, Bayesian statistics and constrained statistical inference.
He was elected to become a member of the Young Academy of the Royal Netherlands Academy of Arts and Sciences (KNAW) and of the Society of Multivariate Experimental Psychology (SMEP). He obtained a VENI (on Integrating background knowledge about traumatic stress experienced after trauma into statistical models assessing individual change over time) and a VIDI (on Experts, their prior knowledge, and the issue of limited data). The ASReview project was awarded with the KNVI- Victorine van Schaickfonds Initiative Award.
Rens obtained his PhD cum laude on the topic of applying Bayesian statistics to real life data at the Methodology and Statistics department at Utrecht University, The Netherlands. His dissertation was received the APA-award for best dissertation of the division of Quantitative and Qualitative Methods. During his PhD, he advocated the interests of PhD-students within the university as chair of the PhD-council Prout. Rens is also past-president of the Early Researchers Union of the European Association of Developmental Psychology. Before his PhD, Rens had completed a research master programme in Development and Socialization of Children and Adolescents, also cum laude.